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This video demystifies how Convex works under the hood for real-time web apps. From a developer’s perspective, it explains Convex’s log-structured storage, versioned indexes, and transaction model that enables strong consistency with high throughput. Viewers see how optimistic concurrency control (OCC) resolves conflicts (e.g., “two users, one item”) while subscriptions deliver instant UI updates over WebSockets. The demo stack includes a React frontend hosted on Netlify/Vercel, a Convex backend running in the Convex Cloud (local Dev on SQLite; cloud on Postgres/MySQL), and a V8 function runtime. Ideal for developers evaluating Convex vs. traditional database wrappers, and anyone designing scalable, real-time CRUD with deterministic server functions. Timestamps [00:00:00] Why Convex is more than a DB wrapper [00:00:11] Live demo: cart updates across tabs [00:00:30] The core question: speed, scale, and correctness [00:00:54] What the video covers (internals roadmap) [00:01:14] Swag House demo app and deployment model [00:02:00] Hosting frontend; Convex client + WebSocket setup [00:02:28] Peeking inside a Convex deployment [00:02:50] Database schema: items and cart_items [00:03:15] Querying items without manual sync logic [00:03:40] Mutation flow for Add to Cart [00:04:30] Local dev: running Convex and SQLite storage [00:04:56] Inspecting the underlying tables [00:05:31] Common misconception: not just Postgres/MySQL tables [00:05:57] Documents table and Convex fields (id, creationTime) [00:06:04] Transaction log as immutable source of truth [00:06:34] Multi-doc updates at a single timestamp (atomicity) [00:07:54] Indexes built on the log for efficient reads [00:08:21] Versioned indexes and point-in-time views [00:09:04] Concurrency scenario: who gets the last hat? [00:10:42] Transactions: batching reads + writes deterministically [00:12:16] The committer: conflict checks against intervening writes [00:13:44] OCC retries and side-effect-free mutations [00:14:57] Read sets powering real-time subscriptions [00:16:18] End-to-end request flow (client ↔ sync worker ↔ runner) [00:18:34] Write path, commit, and query invalidation [00:19:06] Recap and what wasn’t covered [00:19:38] Topics for future deep dives [00:19:49] Wrap-up and next steps Resources written form: https://stack.convex.dev/how-convex-w... also good reading: https://docs.convex.dev/database/adva... Hashtags #convex #databases #transactions #optimisticconcurrency #realtime #websockets #react #javascript #sqlite #postgres #mysql #indexing #scalability #consistency #cloud